Differential time synchronization of intelligent electronic devices

ABSTRACT

In a utility monitoring system, a network of intelligent electronic devices (IEDs), including a master IED that receives master clock information from a global positioning system, includes a differential time synchronization (DTS) algorithm for automatically adjusting the corresponding clocks of each of the IEDs to be synchronized with the master clock information. A controller coupled to the network communicates instructions to the IEDs to collect frequency variation data. A known data alignment algorithm determines a point of alignment between two sets of frequency variation data, and the controller determines based on the data alignment algorithm output a time differential representing a time offset between the IED&#39;s clock and the master clock information. The time differential is communicated to the target IED, which advances or retards its clock based on the time differential.

FIELD OF THE INVENTION

This invention relates generally to methods of time synchronizing clocksof intelligent electronic devices to a common time reference by sendinga time differential to wayward clocks.

BACKGROUND

Normally, a network of intelligent electronic devices (IEDs) willintroduce a delay while messages are communicated through the network.Devices and protocols conventionally attempt to compensate for thisdelay by (a) making the network “fast” (i.e., reducing thecommunications delay to an insignificant proportion of the overallerror), or (b) modeling the network to determine what the delay is andincorporating the estimated delay in the absolute time. Each of theseconventional methods has drawbacks. The first method is not alwayspossible, particularly for wide area networks spanning a largegeographic area. The first method can also be expensive because afaster, high bandwidth, low latency network is needed to maintainaccurate time-synching, but such a network may be entirely too advancedfor an implementation where a low speed, low bandwidth, high latencynetwork would otherwise be entirely sufficient. In the second method, amore accurate time synchronization message can be obtained versus thefirst method, but any variability in the communication latency of thenetwork will increase the time error of the message. Because thecommunication latency variability in IED networks can be and commonly islarger than the acceptable error, the second method may not meet theaccuracy requirements.

Clocks are known to shift over time and even though they may besynchronized at one point in time, eventually they fall out of synch andneed to be resynchronized. In utility systems, it is known tosynchronize the clocks of IEDs by sending data indicative of an absolutetime reference, but this data is susceptible to the same communicationdelays and latencies in the network, so by the time the new timereference is received, the attendant delay in network communications andprocessing creates a slight offset between the device's clock and themaster clock. Synchronization among IEDs in a utility system isimportant at least for critical event reporting and alarming. Whenmultiple events occur very close in time to one another, it is importantto determine which event was critical. Out-of-synch clocks exacerbatethe ability to report accurately sequence-of-events and to diagnoseproblems associated therewith.

What is needed, therefore, is a more accurate method of synchronizingIEDs in a utility system, one that is immune from network or processingdelays and latencies. Aspects of the present disclosure are directed toaddressing this and other needs.

BRIEF SUMMARY

The time synchronization aspects disclosed herein differ fromconventional time synchronization methods used in utility monitoringsystems in that instead of transmitting an absolute time reference todevices whose clocks have drifted away from a reference clock, a timedifferential is sent instead, which is immune from communication andprocessing delays that can introduce an error in the absolute timereference. These aspects eliminate that error and allows wide geographicarea synchronization of numerous devices from a single accurate timesource, which may obtain its reference clock from a global positioningsystem or other reliable source of accurate timekeeping.

The foregoing and additional aspects of the present invention will beapparent to those of ordinary skill in the art in view of the detaileddescription of various embodiments, which is made with reference to thedrawings, a brief description of which is provided next.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other advantages of the invention will become apparentupon reading the following detailed description and upon reference tothe drawings.

FIG. 1 is a functional block diagram of a utility monitoring system thatincorporates a differential time synchronization module according to anaspect of the present disclosure;

FIG. 2 is a flow chart of a clock synchronization algorithm according toan aspect of the present disclosure;

FIG. 3 illustrates a differential time synchronization example showingtwo curves and how the time differential is communicated from acontroller to a target IED whose clock needs to be synchronized with amaster clock; and

FIG. 4 is a flow chart of an exemplary differential time synchronizationalgorithm that includes optional algorithms for further increasing theshort- and long-term accuracy of the time correction.

While the invention is susceptible to various modifications andalternative forms, specific embodiments have been shown by way ofexample in the drawings and will be described in detail herein. Itshould be understood, however, that the invention is not intended to belimited to the particular forms disclosed. Rather, the invention is tocover all modifications, equivalents, and alternatives falling withinthe spirit and scope of the invention as defined by the appended claims.

DETAILED DESCRIPTION

FIG. 1 is a functional block diagram of a utility monitoring system 100that includes an electronic controller 102 coupled to a masterintelligent electronic device (IED) 104 via a conventional network 106,such as the Internet or a private area network. The controller 102 canbe conventionally part of a computer, such as a server. The master IED104 includes a conventional antenna 106 that receives master timeinformation (e.g., any combination of one or more of month, day, year,hour, minute, second, fraction of a second, time zone) from a timesource, such as a global positioning system (GPS) 108. The master IED104 includes a clock 110 that is synchronized with the time informationreceived from the GPS 108 such that the clock 110 and the clock for theGPS 108 report the same time simultaneously. A plurality of IEDs 112-124are also coupled to the controller 102 via the network 106. The IEDs112-124 also each include a clock, such as the clock 126 shown in theIED 114. The other clocks for the other IEDs 116-124 are not shown forease of illustration. The controller 102 includes a conventionalelectronic memory device that stores a data alignment algorithm 128 asdescribed in commonly assigned and co-pending U.S. application Ser. No.11/174,099, filed Jul. 1, 2005, entitled “Automated Precision Alignmentof Data in a Utility Monitoring System,” the content of which isincorporated herein by reference in its entirety. Optionally, a dataalignment algorithm 130 can also or alternately be stored in a memorydevice on any of the IEDs 112-124, such as the IED 114 shown in FIG. 1.Although the master IED 104 is shown receiving a reference clock timefrom a GPS 108, in other implementations, a reference clock time can bebased upon the network time protocol (NTP) or any other reliable sourceof timekeeping.

Briefly, the data alignment algorithm 128, 130 aligns data measured byIEDs coupled to a monitoring system. The algorithm 128, 130 receives, atthe controller 102, which is remote from the IEDs 104, 112-124,reference signal data from a master IED 104. The reference signal datarepresents frequency/amplitude/phase variations in a characteristic ofthe utility being measured by the master IED 104 for a predeterminednumber of cycles. For example, in the case of a power monitoring system,the frequency variations occur in the current or voltage from anelectric grid. The master IED 104 stores a reference count associatedwith each of the cycles sensed by the master IED 104. The algorithm 128,130 receives, at the controller 102, second signal data from the IED114. The second signal data also represents frequency/amplitude/phasevariations in a characteristic (e.g., current, voltage) of the utility(e.g., power) being measured by the IED 114 for a predetermined numberof cycles. The IED 114 stores a second count associated with each of thenumber of cycles sensed by the IED 114. The algorithm 128, 130automatically aligns the reference signal data with the second signaldata to a common reference point in the respective current or voltagesensed by the master IED 104 and the IED 114 by: computing correlationcoefficients each produced by a cross-correlation algorithm based on atleast part of the reference signal data and at least part of the secondsignal data until one of the correlation coefficients produced by thecross-correlation algorithm satisfies a criterion; and in response toone of the correlation coefficients satisfying the criterion,associating the reference count associated with the common referencepoint with the second count associated with the common reference point.The criterion can include the correlation coefficient corresponding to amaximum correlation coefficient produced by the cross-correlationalgorithm. The common reference point can correspond to a zero crossingin the measured current or voltage. The reference count and the secondcount can each correspond to the cycle count number associated with thecommon reference point. From the difference in cycle counts, a timedifferential can be calculated in seconds by dividing the cycle countdifference by the fundamental frequency of the monitoring system (e.g.,60 Hz). For example, a cycle count offset of 15 cycles would result in atime differential of 250 milliseconds. The lagging clock would have tobe increased by 250 milliseconds to bring both clocks into mutualsynchronization.

When the clock 110 of the master IED 104 and the clock 126 of the IED114 are not synchronized (i.e., reporting different time information atthe same moment in time), such that one of the clocks lags or leads theother, a differential time synchronization (DTS) module or algorithm 132as described further herein determines from the output of the dataalignment algorithm 128, 130 a difference indicative of the offset intime between the two clocks and causes that difference to becommunicated to the clock 126, which might be lagging or leading theclock 110 of the master IED 104. A number of significant problems canoccur when the clocks of the IEDs 112-124 are not synchronized.Reporting and analysis of the measured data from the IEDs 112-124becomes difficult, unwieldy, inaccurate, and time-consuming. Forexample, when two events or anomalies occur on the monitoring systemnearly simultaneously, a time offset between clocks can result indifferent IEDs 112-124 reporting the same event at different times,leading to confusion as to which of the two events are actually beingreported. It is important to emphasize that the DTS algorithm 132 doesnot send the absolute time reference, but rather a difference or timeoffset indicative of how much time the target device needs to add orsubtract from its own clock to synchronize its clock with the clock 110of the master IED 104. As a result, the synchronization occursindependently of any communication or other processing delays in thenetwork 106 between the master IED 104 and the target IED 112-124.Although the DTS algorithm 132 is shown stored in a memory of the masterIED 104, the DTS algorithm 132 can also be stored in a memory of thecontroller 102 or in a memory of any of the other IEDs 112-124 in themonitoring system 100.

With reference to FIG. 2, the controller 102 communicates an instructionto the master IED 104 and the IEDs 112-124 to begin collecting dataindicative of frequency or amplitude or phase variations needed for thedata alignment algorithm 128, 130 (200). Preferably, the IEDs 112-124store data indicative of variations in the fundamental frequency,because this frequency remains unchanged throughout the system.Alternately, the master IED 104 communicates an instruction to the IEDs112-124 to begin collecting frequency or amplitude or phase variationdata. The controller 102 receives the frequency or amplitude or phasevariation data from the master IED 104 and from the IEDs 112-124 (202).The controller 102 executes the data alignment algorithm 128 todetermine a point of alignment between the frequency or amplitude orphase variation data from the master IED 104 and one of the IEDs 112-124(204). In one example, a cycle count offset is determined by the dataalignment algorithm 128, and this cycle count offset is converted into acorresponding time based upon the period of each cycle (typically about60 Hz in North America). The time corresponding to the cycle countoffset between the point of alignment between the two data sets is thetime difference between the two clocks. The controller 102 communicatesthis time differential, which can be a positive or a negative number,via the network 106 to the target IED (e.g., IED 114) (206), and thetarget IED 114 adjusts its clock 126 by the time differential (208). Asa result, the clock 126 of the IED 114 and the clock 110 of the masterIED 104 are synchronized to the same absolute time reference.

In FIG. 3, a differential time synchronization example is illustratedshowing two curves 300, 302. The curve 300 represents frequencyvariation data from the master IED 104, and the curve 302 representsfrequency variation data from the target IED 114. Due to delays andother latencies in the monitoring system 100, the IEDs 104, 114 do notreceive time synchronization commands at the same moment in time. Thiscan result in a difference in the time indicated by the clock in IED 104and the clock in IED 114. As a result of this time difference, IED 104records a frequency variation at time t1, whereas IED 114 records thatsame frequency variation at a later time, t2. In an embodiment, thesetimes can be stamped within each IED with a corresponding cycle count,which represents the number of times the IED has recorded a zerocrossing (positive or negative going) in the measured signal that isindicative of a characteristic of the utility being monitored by themonitoring system 100. The data alignment algorithm 128, 130 finds thispoint of correlation (points 304, 306 on the curves 300, 302), andproduces data indicative of these two points (such as a time referenceor a cycle count). The controller 102 (or the IED 114 in implementationswhere the data alignment algorithm 130 is executed in the IED 114)determines from these points 304, 306 a time differential, Δt, bysubtracting the time references corresponding to the two points ordetermining an offset between the respective cycle counts from the IEDs104, 114 and calculating a corresponding time differential from theoffset based upon the known periodicity of the cycles. For example, ifthe cycle count offset is 60, such that one IED needs to advance orretard its clock by 60 cycles, and the fundamental frequency is 60 Hz,then the time differential Δt is one second. This time differential Δtis communicated from the controller 102 to the target IED 114, whichadjusts its clock 126 accordingly. Note that Δt can be positive ornegative, depending upon whether the clock 126 leads or lags the clock110 of the master IED 104. Alternately, the controller 102 can send thecycle count offset (in this example, 60) directly to the IED 104, whichlooks at the sign of the offset and adjusts its clock accordingly. Forexample, a positive 60 cycles would cause the IED 104 to advance itsclock by 1 second; a negative 60 cycles would cause the IED 104 todecrement its clock by 1 second.

The period of time for collecting the frequency/amplitude/phasevariation data (referred generally as “variation data”) should be atleast equal to the delay in the network 106 between the master IED 104and the target IED 114 plus the amount of time needed to obtaincorrelation using the data alignment algorithm 128 between the variationdata collected by the IEDs 104, 114 to the required accuracy. If thetime period of collection is too small, the controller 102 will not beable to locate a point of correlation in the variation data.Conventional algorithms can be used to determine the approximatecommunication delay through the network 106 and to adjust the timeperiod of collection accordingly. Without this adjustment, a larger setof variation data would be required from the IEDs, consuming bandwidththrough the network.

As mentioned above, the data alignment algorithm 130 can be stored inand executed by IED 114. In this example, the master IED 104 and theother IEDs 112, 116-124 in the monitoring system 100 communicate theirrespective variation data across the network 106 to the IED 114. Notethat more than one IED in the system 100 can execute the data alignmentalgorithm. The IED 114 executes the correlation sequence algorithms fromthe data alignment algorithm 130 against its own variation data that theIED 114 has collected locally to calculate the required time correction.Advantageously, local execution in the IEDs of the data alignmentalgorithm 130 reduces bandwidth in the network 106 as the data needed torun the correlation algorithms need not be communicated among each IEDthat requires time synchronization and also allows the IEDs to be timesynchronized simultaneously. In other words, when the data alignmentalgorithm 128 is executed by the controller 102, two sets of variationdata need to be communicated from the master IED 104 and the target IED.When the data alignment algorithm 130 is executed locally at the IED114, only one set of variation data needs to be communicated from themaster IED 104 to the IED 114.

The raw frequency/amplitude/phase variation data can be resampled to asmaller time interval, so instead of using one cycle frequencymeasurements, for example, a half cycle (or any larger or smallerperiod) frequency measurements can be used. Resampling the variationdata to a smaller time interval advantageously (1) increases the numberof points that the correlation algorithms in the data alignmentalgorithm use and thus helps to increase the precision of the timedifferential calculation; (2) allows the use of IEDs with differentsampling rates in the monitoring system 100; and (3) reduces the numberof points used in the correlation calculations to allow the controller102 to determine what ranges of raw sample sets have high correlationand then to focus detailed correlation calculations on those specificranges.

First, by increasing the number of points that the correlationalgorithms use, a more precise time differential can be calculatedbecause a smaller sample period increases the accuracy of the calculatedtime difference. Second, IEDs with different sampling rates can reducethe cost of the monitoring system 100 as a whole. For example, assume abasic IED with a frequency sampling/calculation rate of once every fourcycles versus a more advanced IED with a calculation rate of once everycycle. By resampling the four-cycle capable device, its variation datais resampled to one sample point per cycle. Without resampling, the rawvariation data, only every fourth cycle sample point could be used fromthe more capable IED. With resampling, the variation data from the lesscapable, four cycle device is resampled to one sample point for eachcycle and these sample points can be correlated one-to-one with the morecapable device directly. For a device that samples once every fourcycles, the step size of the time differential is about 66.6milliseconds (for a 60 Hz system), whereas the step size is about 16.6milliseconds for a device that samples once per cycle. Third, byreducing the number of points, the computational complexity of runningthe correlation algorithms is reduced by performing the high-resolutioncalculations on a subset of the raw variation data samples. Thus, thesecalculations can be performed on cheaper, less capable IEDs, whichreduces the overall cost of the monitoring system 100. Sections of thevariation data from both sample sets that are highly correlated areidentified, and those sections are resampled to smaller time domainsteps to increase the absolute time accuracy of the individual cycles.As a result, the accuracy of the time differential measurement between apair of IEDs is increased.

Resampling involves calculating intermediate samples between themeasured samples of the raw variation data. As those of ordinary skillin the art will appreciate, resampling is essentially an interpolationtechnique that estimates with varying levels of accuracy where missingsamples would occur. Any one of numerous conventional resamplingalgorithms can be used for this purpose with various tradeoffs betweenthe amount of CPU cycles required for the calculations, changes to thefrequency spectrum of the sample set, and changes to the time domainvalues.

In a further implementation, the controller 102 or one of the IEDs inthe monitoring system 100 tracks what time offsets have historicallybeen sent to a particular IED in the monitoring system 100. In thismanner, the controller 102 or the IED can calculate an error rate of aclock and automatically apply a corrective factor to the clock tocompensate independent of the differential time synchronizationalgorithm 132. As the monitoring system 100 builds a database ofhistorical offsets (time differential values) that have been sent to aparticular device, the clock drift can be estimated with increasingaccuracy, assuming that the conditions causing the clock drift do notchange. As a result, fewer time corrections need to be sent to an IEDover time, and the size and frequency of required time corrections willdiminish over time. Fewer time corrections advantageously consumes lessbandwidth and processing power to maintain the accuracy of an IED'sclock within an acceptable error tolerance. Reducing the size andfrequency of time corrections advantageously causes fewerdiscontinuities to occur in an IED's clock over time. Discontinuitiescan cause significant accuracy issues in IEDs measuring time-dependentparameters such as energy or power. Any accuracy issues with energy orpower measurements can result in lost revenue for market segments suchas utilities.

FIG. 4 is an exemplary differential time synchronization algorithm 400that includes optional algorithms for further increasing the short- andlong-term accuracy of the time correction. The DTS algorithm 400 can bepart of the DTS module 132 and stored with the controller 102 or in theIED 114. The DTS algorithm 400 collects diagnostic data to provide anindication as to when an IED's clock is drifting out of definedspecifications so that the IED can be serviced or replaced before theclock drift becomes unacceptably high.

The server (controller 102) triggers requests from the IEDs 112-124 fortheir respective variation data to be correlated in the monitoringsystem 100 (402). How often the controller 102 triggers these requestscan be based upon the time the last time differential was communicated.A simple method is for the controller 102 to trigger these requests on aperiodic basis. Preferably, the controller 102 calculates when theuncorrected clock drift, based on previous executions, will be largeenough to warrant a correction. Over time, as the IED is characterizedmore accurately, this period can be increased to an amount proportionalto the total of the uncharacterized errors. The variation data samplesto be correlated are stored on each IED 112-124 (404). The IED sends itsvariation data to be correlated and optionally its historical adjustmentdata to the server (controller 102) (406). The historical adjustmentdata corresponds to a historical account of the time differential valuesby which that IED's clock has been adjusted. The variation data frompairs of IEDs are analyzed statistically to find relevant correlationsbetween the points in the variation data samples and a clock time offsetis calculated from the respective points of correlation (408). Thecorresponding time offsets are sent to the IEDs whose clocks need to beadjusted (410). The IED changes its clock by an amount corresponding tothe offset (time differential) (412).

In the optional algorithm 414, the IED temperature and clock drift aremonitored to evaluate a clock drift in the IED's clock. The algorithm414 stores the time-stamped temperature value in a memory of the IED(418) periodically or based upon whether the IED's temperature haschanged from the last stored value by some predetermined amount (416).The temperature value can be used by the DTS algorithm 132 to makefurther adjustments to the time differential sent to a target IED. Eachtime a time differential is communicated to the IED, the algorithm 414stores the time differential value in the memory of the IED for laterretrieval and analysis (426). The algorithm 414 analyzes the clock driftover time and compares the clock drift against a conventional clockdrift model (420). Based on this comparison, the algorithm 414determines whether the clock drift is acceptable (422), and, if not,notifies the user of a problem with the clock drift (424) by displayingan indication of such on a conventional video display (not shown)coupled to the controller 102 or by communicating an electronic message,such as an email, text message, or pager message, to a remote device.The indication informs the user about the need to replace the IED or toservice it. This determination can be based on the time offsets, thedate and time that they occurred, the temperature of the IED, and theclock adjustments made by the IED from the clock model. This optionalalgorithm 414 helps to avoid gradual and sudden degradation of the IEDclock.

In an alternate embodiment, the IEDs 112-124 continually compare clockdrift over time against a conventional clock drift model to determine adrift correction factor required to maintain the accuracy of the IEDs'clock. The IEDs 112-124 apply the drift correction factor to the clockin order to minimize clock drift, therefore minimizing the frequency oftime corrections required from the controller 102. Temperature can havean impact on clock drift, and the IED temperature can be incorporatedinto the conventional clock drift model.

It should be noted that the algorithms 128, 130, 132 illustrated anddiscussed herein as having various modules which perform particularfunctions and interact with one another. It should be understood thatthese modules are merely segregated based on their function for the sakeof description and represent computer hardware and/or executablesoftware code which is stored on a computer-readable medium forexecution on appropriate computing hardware. The various functions ofthe different modules and units can be combined or segregated ashardware and/or software stored on a computer-readable medium as aboveas modules in any manner, and can be used separately or in combination.

Although a controller 102 is shown and described as carrying out variousfunctions, it should be understood that any of these functions can becarried out by the master IED 104 or any of the IEDs 112-124 shown inFIG. 1. Likewise, any of the functions carried out by the master IED 104or by any of the IEDs 112-124 can be carried out by the controller 102,such as the DTS algorithm 132.

While particular embodiments and applications of the present inventionhave been illustrated and described, it is to be understood that theinvention is not limited to the precise construction and compositionsdisclosed herein and that various modifications, changes, and variationscan be apparent from the foregoing descriptions without departing fromthe spirit and scope of the invention as defined in the appended claims.

1. A method of synchronizing respective clocks of intelligent electronicdevices (IEDs) in a utility monitoring system, comprising: receiving, ata controller, respective signal data representing frequency or amplitudeor phase variations in a characteristic of a utility measured by each ofat least two of the IEDs; automatically determining, based on acorrelation algorithm applied to the signal data from the two IEDs, adifference between a first occurrence of a point in the signal data froma first of the two IEDs is measured and a second occurrence of the samepoint in the signal data from a second of the two IEDs is measured; andcommunicating time differential data indicative of the difference to oneof the two IEDs to cause the one of the two IEDs to adjust a clock by atime amount corresponding to the time differential data.
 2. The methodof claim 1, wherein the difference is a time difference, the firstoccurrence corresponds to a first time, and the second occurrencecorresponds to a second time that is earlier or later than the firsttime.
 3. The method of claim 1, wherein the difference is a cycle countdifference, the first occurrence corresponds to a first cycle count, andthe second occurrence corresponds to a second cycle count that isdifferent from the first cycle count, a cycle count representing anumber of full cycles measured by a corresponding one of the IEDs of aperiodically changing characteristic of the utility being monitored. 4.The method of claim 3, wherein the periodically changing characteristicis current or voltage.
 5. The method of claim 1, wherein the utilitymonitoring system is a power monitoring system, and wherein at leastsome of the IEDs are power meters.
 6. The method of claim 1, wherein thecontroller is in one of the IEDs.
 7. The method of claim 1, furthercomprising resampling, at a rate faster or slower than a rate that thesignal data is sampled, the signal data measured by one of the two IEDsto produce resampled signal data, wherein the automatically determiningis carried out based on a correlation algorithm applied to the resampledsignal data from the one of the two IEDs and the signal data from theother of the two IEDs.
 8. The method of claim 1, further comprising:storing a plurality of historical time differential data communicated tothe one of the two IEDs and determining therefrom an error rate of theclock of the one of the two IEDs; and at the one of the two IEDs,automatically compensating the clock as a function of the error rate. 9.The method of claim 1, further comprising comparing a clock drift of theclock to a clock drift model; responsive to the comparing resulting inthe clock drift exceeding a threshold, providing an indication of theclock drift.
 10. The method of claim 1, further comprising adjusting theclock based on a clock drift model that incorporates an ambienttemperature of at least one of the two IEDs.
 11. The method of claim 1,wherein the correlation algorithm includes: computing correlationcoefficients each produced by a cross-correlation algorithm based on atleast part of the first and second signal data until one of thecorrelation coefficients produced by the cross-correlation algorithmsatisfies a criterion; and in response to the one of the correlationcoefficients satisfying the criterion, associating the first occurrenceof the point in the first signal data with the second occurrence of thesame point in the second signal data at the point at which thecorrelation coefficient satisfies the criterion.
 12. A method ofsynchronizing respective clocks of intelligent electronic devices (IEDs)in a power monitoring system, wherein one of the IEDs is a master IED,comprising: receiving, at the master IED, master time information from atime source; storing, in a memory of the master IED, the master timeinformation; receiving, at a controller, respective signal datarepresenting frequency variations in a current or voltage measured bythe master IED and another of the IEDs termed a target IED;automatically determining, based on a data alignment algorithm appliedto the signal data from the master IED and the target IED, a timedifference between a first occurrence of a point in the signal datameasured from the master IED and a second occurrence of the same pointin the signal data measured from the target IED; and communicating timedifferential data indicative of the time difference to the target IED tocause the target IED to adjust a clock by a time amount corresponding tothe time differential data.
 13. The method of claim 12, wherein thecontroller is in the first IED.
 14. The method of claim 12, wherein thetime source is a global positioning system.
 15. The method of claim 12,further comprising resampling, at a rate faster than a rate that thesignal data is sampled, the signal data measured by the target IED toproduce resampled signal data, wherein the automatically determining iscarried out based on the correlation algorithm applied to the resampledsignal data from the master IED and the signal data from the target IED.16. The method of claim 12, further comprising: storing a plurality ofhistorical time differential data communicated to the target IED anddetermining therefrom an error rate of the clock of the target IED; andat the target IED, automatically compensating the clock as a function ofthe error rate.
 17. The method of claim 12, further comprising comparinga clock drift of the clock of the target IED to a clock drift model;responsive to the comparing resulting in the clock drift exceeding athreshold, displaying on a video display an indication of the clockdrift.
 18. The method of claim 12, further comprising: determiningwhether a temperature of the target IED has changed compared to aprevious temperature reading; if the determining whether the temperaturehas changed results in a temperature change, inputting the temperaturechange into a clock drift model; and adjusting the clock of the targetIED based on the clock drift model.
 19. The method of claim 1, whereinthe correlation algorithm includes: computing correlation coefficientseach produced by a cross-correlation algorithm based on at least part ofthe first and second signal data until one of the correlationcoefficients produced by the cross-correlation algorithm satisfies acriterion; and in response to the one of the correlation coefficientssatisfying the criterion, associating the first occurrence of the pointin the first signal data with the second occurrence of the same point inthe second signal data at the point at which the correlation coefficientsatisfies the criterion.